class_docstr: :param trace_dist: a TracePosterior instance representing a Monte Carlo posterior
  
  Marginal histogram distribution.
  Turns a TracePosterior object into a Distribution
  over the return values of the TracePosterior's model.
code: def log_prob(self, val):
      d, values_map = self._dist_and_values()
      if torch.is_tensor(val):
          value_hash = hash(val.cpu().contiguous().numpy().tobytes())
      elif isinstance(val, dict):
          value_hash = hash(self._dict_to_tuple(val))
      else:
          value_hash = hash(val)
      return d.log_prob(
          torch.tensor([list(values_map.keys()).index(value_hash)])
      )
  
imports: import collections
  import functools
  import queue
  import torch
  import pyro.distributions
  import pyro.poutine
  from pyro.infer.abstract_infer import TracePosterior
  from pyro.poutine.runtime import NonlocalExit
label_desc: Use image node_id 4 for calling the HashingMarginal obj's underlying member method code with example usage: obj.log_prob(val) and returns: d